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      How Assumptions and Preferences Can Affect Patient Care: An Introduction to Implicit Bias for First-Year Medical Students

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          Abstract

          Introduction

          Instruction in implicit bias is becoming prevalent across the spectrum of medical training. Little education exists for preclinical students, and guidance for faculty to facilitate such education is minimal. To address these gaps, we designed and delivered a single session for incoming first-year medical students and developed a facilitator training program.

          Methods

          One faculty member delivered a 1-hour, multimedia, interactive lecture to all first-year medical students. Students subsequently met in small groups with trained facilitators. Activities included reflection, guided debriefing, and strategy identification to become aware of when they might be making an assumption causing them to jump to a conclusion about someone. The program evaluation consisted of aggregated student strategies and facilitator feedback during postsession debriefs, both analyzed through thematic analysis.

          Results

          We delivered instruction to 1,098 students. Student strategies resulted in three themes: (1) humility, (2) reflection, and (3) partnering. The postsession debriefs uncovered opportunities to enhance the session. Lessons learned included presenting material to an entire class at once, allowing students to engage in dynamic discussion in the small groups, eliminating anonymous polling in the small groups, and highlighting management of implicit bias as essential to professional development.

          Discussion

          Our instructional design enabled first-year medical students to identify at least one strategy to use when implicit biases are activated. The large-group session was deliverable by one faculty member, and volunteers successfully facilitated small-group sessions after only one training session, making this model a feasible innovation to reach an entire medical school class at the same time.

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          Most cited references39

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            Implicit Bias among Physicians and its Prediction of Thrombolysis Decisions for Black and White Patients

            Context Studies documenting racial/ethnic disparities in health care frequently implicate physicians’ unconscious biases. No study to date has measured physicians’ unconscious racial bias to test whether this predicts physicians’ clinical decisions. Objective To test whether physicians show implicit race bias and whether the magnitude of such bias predicts thrombolysis recommendations for black and white patients with acute coronary syndromes. Design, Setting, and Participants An internet-based tool comprising a clinical vignette of a patient presenting to the emergency department with an acute coronary syndrome, followed by a questionnaire and three Implicit Association Tests (IATs). Study invitations were e-mailed to all internal medicine and emergency medicine residents at four academic medical centers in Atlanta and Boston; 287 completed the study, met inclusion criteria, and were randomized to either a black or white vignette patient. Main Outcome Measures IAT scores (normal continuous variable) measuring physicians’ implicit race preference and perceptions of cooperativeness. Physicians’ attribution of symptoms to coronary artery disease for vignette patients with randomly assigned race, and their decisions about thrombolysis. Assessment of physicians’ explicit racial biases by questionnaire. Results Physicians reported no explicit preference for white versus black patients or differences in perceived cooperativeness. In contrast, IATs revealed implicit preference favoring white Americans (mean IAT score = 0.36, P < .001, one-sample t test) and implicit stereotypes of black Americans as less cooperative with medical procedures (mean IAT score 0.22, P < .001), and less cooperative generally (mean IAT score 0.30, P < .001). As physicians’ prowhite implicit bias increased, so did their likelihood of treating white patients and not treating black patients with thrombolysis (P = .009). Conclusions This study represents the first evidence of unconscious (implicit) race bias among physicians, its dissociation from conscious (explicit) bias, and its predictive validity. Results suggest that physicians’ unconscious biases may contribute to racial/ethnic disparities in use of medical procedures such as thrombolysis for myocardial infarction.
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              Transformative Learning: Theory to Practice

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                Author and article information

                Journal
                MedEdPORTAL
                MedEdPORTAL
                mep
                MedEdPORTAL : the Journal of Teaching and Learning Resources
                Association of American Medical Colleges
                2374-8265
                2021
                28 June 2021
                : 17
                : 11162
                Affiliations
                [1 ] Professor, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine
                [2 ] Research Assistant, Department of Medicine, Albert Einstein College of Medicine
                [3 ] Principal Associate, Department of Family and Social Medicine, Albert Einstein College of Medicine
                [4 ] Professor, Department of Epidemiology and Population Health, Albert Einstein College of Medicine; Professor, Department of Medicine, Albert Einstein College of Medicine; Associate Dean for Clinical Research Education, Albert Einstein College of Medicine
                Author notes
                Corresponding author: crgonzal@ 123456montefiore.org
                Author information
                https://orcid.org/0000-0002-9779-6548
                Article
                11162
                10.15766/mep_2374-8265.11162
                8236500
                34263027
                a97eb7d4-8340-44da-8a44-61883b0b3337
                © 2021 Gonzalez et al.

                This is an open-access publication distributed under the terms of the Creative Commons Attribution-NonCommercial license.

                History
                : 26 October 2020
                : 4 April 2021
                Page count
                Tables: 2, References: 41, Pages: 8
                Categories
                Original Publication

                implicit bias,unconscious bias,health care disparities,faculty development,diversity and inclusion,health equity

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